Episode 7.4: Your AI Marketing Learning Journey
In this episode, we unpack the essential AI marketing learning journey, providing a clear roadmap for marketers to navigate this evolving landscape. We’ll explore the core modules, from foundational AI concepts to practical applications across content creation, SEO, social media, email, and influencer marketing. Learn how to build a winning AI strategy, measure ROI, and stay ahead of the curve in this dynamic field.
Transcript of Episode 7.4: Your AI Marketing Learning Journey
Alright, welcome back to the Deep Dive. Today we’re really jumping into something well. Pretty essential for marketers right now, the AI marketing learning journey. Yeah, absolutely. We’ve gathered some great material that essentially maps it all out. Yeah. You know, from the real foundational stuff about ai, all the way to actually applying it day to day and content. SEO social media email. Mm-hmm. Even influencer marketing. Exactly. It’s almost like, uh, getting the inside track on how AI is shaking things up. We’re looking at tools you can actually use like right now. Right? And crucially how to build a proper strategy around them. And maybe most importantly, figuring out if all this AI stuff is actually. You know, giving you a return, Uhhuh.
So the mission today is really to unpack the core modules of this journey so you listening can get a clear sense of what you need to know to, well keep up. Okay. So where does this journey kick off? I’m guessing we start with the basics. Like when we say AI and marketing, what are we even talking about at the start? Yeah, you got it. It begins with nailing down some core AI concepts. First up is understanding the AI stack. Think of it like layers. Okay? At the top you’ve got artificial intelligence itself. The big idea of making machines smart. Then, uh, one level down is machine learning or ml.
That’s where AI learns from data instead of needing explicit instructions for everything, right, learning by example. Sort of. Exactly. And then deep learning dl, that’s a more complex type of ml using these things called neural networks. It’s kinda like the difference between basic legos and you know, the super advanced technic sets. Ah, okay. Good analogy. Mm-hmm. So AI is the goal. ML is a method, DL is an advanced method. Got it. Pretty much. And then you get to the application stuff like Natural Language Processing, NLP and Computer Vision for marketers. NLP is, well, it’s huge. Hmm.
It’s how AI understands and uses human language. Think chatbots, answering customer questions or tools, analyzing social media comments to see if people feel positively or negatively about your brand. That’s sentiment analysis. And it’s also behind a lot of the AI content creation and SEO tools. We’ll probably talk about, imagine sifting through thousands of reviews manually versus having NLP do it in seconds. Yeah. NLP definitely sounds like a game changer for understanding people. Yeah. So once we’ve got those fundamentals down, where does the learning journey take us? Content creation seems like the next logical step, right? Yeah. We saw that in the ai. Content and SEO course.
Yeah, the AI Marketing Advantage course. That’s exactly right. A big chunk of the journey is dedicated to how AI is transforming content, starting with, uh, text generation. This is where large language models or LLMs come in. LLMs. Okay. Yeah. Picture an LLM, like a gigantic digital library just stuffed when texts from everywhere. You give it a prompt, a set of instructions, right? And it uses all that knowledge to generate text. Could be blog posts, maybe you know how to choose the right coffee maker or. Catchy ad copy, like boost your sales. Mm-hmm. Social media posts, product descriptions, emails, even rough scripts for videos. It sounds like having a super fast writing assistant on call 2, 4 7, but um, how good is the output really? Is it usable straight away? It can be surprisingly good. Yeah. But it’s definitely not perfect, not magic.
The learning journey points out specific tools like you’ve got Copy AI. Often better for shorter stuff. Ads, social posts. Yeah. And then there’s Jasper (formerly Jarvis), which tends to be geared towards longer form content. They have different costs, trials. You need to see what works for you. Makes sense. But the really interesting part is how you guide these tools. It’s all about the prompt. You need to be really clear. The journey covers things like few shot prompting. What’s that? That’s where you give the AI a few examples of what you want. Like here are three tweets I like write one in a similar style. Ah, okay. Giving it examples Exactly. And chain of thought prompting where you ask it to sort of think out loud, which can sometimes get you better and more reason results. It forces it to break down the steps, so it’s less about just telling it what to write and more about showing it how you want it written precisely, which leads straight into advanced prompt engineering. This is a key skill. The learning materials really stress being super clear.
Specific, giving context, right? Setting constraints like word count or tone. There are frameworks mentioned like the five W is an H, who, what, when, where, why, how, or thinking of the AI as an actor with a specific role or personality. Hmm, interesting. Like telling it to write as a skeptical expert or something. Exactly. And a core concept here is the prompt test, refine loop. You write a prompt, see the output. It’s probably not quite right. Yeah, usually. So you tweak the prompt. Maybe make it more specific. Add a constraint. Try again, refine it. Say you asked for a social media post about AI and marketing. Too broad. Right? Right. So you refine it. Write a 140 character tweet for Twitter. Listing three benefits of AI for social media. Pros use relevant hashtags, adopt an excited tone much better. And I guess different ais might react differently even to the same refined prompt. Oh, absolutely.
A big model like GPT four has seen, you know, a massive amount of data. It might give you something more nuanced than say, Copy AI, which might be optimized for speed or a specific marketing style. It really proves the old saying, you know, garbage in, garbage out. J go. Yeah. If your prompts are lazy or vague, well you’ll get lazy or vague results like a bad web search. Okay, makes perfect sense. Need to be good instructor. But what about quality and crucially originality. That’s always the big worry with AI content. Totally. And the learning journey tackles this head on. It hammers home. You most fact, check. AI output always, right? It talks about tools and methods for checking facts and also for spotting potential plagiarism, giving credit where it’s due uhhuh. But the biggest point it makes is that AI is a collaborator, not a replacement. You the human need to layer in your expertise, your insights, your brand’s, unique voice. AI might draft something or speed up research, but the human touch, that’s what adds the real value and originality. AI is the assistant, not the author. That framing feels right. What about visuals?
We hear so much about AI images and video now. Yep. The journey covers that too. For images, it mentions tools like DALL-E 2 / DALL-E 3 (OpenAI) that’s often good for photorealistic stuff. Midjourney tends to be more artistic, sometimes quite wild. Okay. There’s Craiyon (formerly DALL-E mini), which is free. Good for quick ideas maybe. And even Canva has an AI image generator built in. Now I that, and for video, you’ve got things like Synthesia, which uses AI avatars. Those talking heads, Lumen5 can turn blog posts into simple videos. Pictory is good for chopping up longer videos into social clips. Nvidia offers more complex editing features. Lots of options for sure, but the key takeaway here is strategy. Why are you making this image or video? Is it for brand awareness? Leads, sales, different tools, suit different goals? And it suggests looking for content gaps.
Like maybe you have a really popular blog post on, say, beginner’s guide to SEO, but it has a high bounce rate. Maybe an AI assisted video could explain it better. Hmm. Smart application. Okay, so AI in content is massive. Where next SEO seems tightly connected. It really is. AI in SEO is a big module pulling from both the SEO course and the Advantage course, the journey points out how AI can seriously level up keyword research. How so? Well, it’s great at finding those long tail keywords, the longer, more specific search phrases people use when they’re closer to buying. Right. Like best waterproof, running shoes for wide feet under a hundred dollars. Exactly. Not just running shoes. AI tools can also uncover related. Semantic keywords and help figure out the intent behind a search. Why is someone searching for this? Tools like Surfer SEO, MarketMuse NeuronWriter get mentioned here.
So digging deeper than just the main keywords. What about optimizing the actual content we write based on those keywords? Yeah, that’s the next piece. The journey explains how AI tools analyze the page is already ranking high for your target keyword. Okay? They look at what terms they use, how they structure the content, the headings, and then they give you suggestions for your own content. Some even give you a score, like your content is 75% optimized a score. Interesting and technical. SEO, the backend stuff. Yep. AI helps there too. It can automate finding those technical glitches that Google hates broken links, pages, the search engine can’t crawl properly. Slow loading speed. Whether it works well on mobile security issues like H-T-T-P-S, AI tools can flag these much faster than manual checks. Wow. Okay. That could save a lot of headaches. Let’s shift to social media.
How’s AI fitting in there? We saw the AI for Social Media course touched on this. AI is really weaving itself into social media marketing for content creation. Again, you’ve got tools like ChatGPT (OpenAI) or Canva Magic, right? Helping draft captions, headlines. Yeah. And tools like Feedly using AI to find trending topics or content you could repurpose, but same caveat as before. Always refine it. Add your brand’s personality, right? The human touch, definitely beyond creation. AI is huge for social listening, analyzing all those mentions, comments, shares to understand sentiment in real time. Sentiment Analysis Tools Are people happy, upset? Who are your biggest fans? Who’s complaining?
So moving beyond just counting likes to understanding the why. Exactly, and it helps with audience insights too. AI can look beyond basic demographics using tools like say, spark Toro or Audiense to find groups based on shared interests, online behavior, what content they engage with. You can build these dynamic audience segments that change as people’s actions change. That sounds powerful for targeting. It is, and that leads into advertising. AI is driving things like automated targeting on Meta and Google Advantage, plus SMART bidding. Dynamic creative optimization, or DCO, where AI mixes and matches headlines, images, calls to action to find the best combos. Plus AI helps manage bids to maximize your ROI. Wow. And finally, it touches on community management and customer service. Think AI chatbots maybe built with something like ManyChat handling common questions, offering instant support, maybe even qualifying leads before handing off to a human, like a superpowered social media assistant.
Okay. What about email? Yeah. Still a massive channel for many. Oh yeah. Email’s not going anywhere, and AI is making it smarter. The learning journey, especially referencing the AI for email and CRM marketing course really emphasizes the strategic value. AI lets you scale personalization way beyond just using someone’s first name. Hyper-personalization, right? Exactly. Tailoring content based on deep data insights plus realtime optimization. Adjusting send times for individuals showing dynamic content within the email itself. This all leads to better ROI. Better engagement. More loyalty. So which tools help with this? The journey mentions a mix. You’ve got the big platforms like Mailchimp, Constant Contact, ActiveCampaign, HubSpot, many our baking AI features in predicting purchase likelihood, optimizing send times. Okay. Then more specialized tools like FRAZEE for ai, language generation, Seventh Sense for Send Time optimization, Optimove (formerly Optimail) . They focus on specific AI functions like predictive content, workflow automation, realtime personalization within the email body. That depth of personalization sounds amazing, maybe a bit complex.
How does AI actually do that? Good question. The journey breaks it down into, um, three main types, behavioral personalization. That’s based on past actions. What did they click, what did they buy? So you get smarter product recommendations, triggered emails for card abandonment, that kind of thing. Right. Based on what they did. Then there’s contextual personalization. Mm-hmm. That uses realtime info. Where are they opening the email? What device is it raining there? So you might show localized promotions or optimize the layout for mobile on the fly. Okay, based on what’s happening now. Yep. And finally, predictive personalization. This uses historical data to guess future needs. Suggesting products they might like next. Re-engaging people before they go inactive for predicting what content topics they’ll be interested in. Wow. Behavioral, contextual, predictive. Got it. And it also covers dynamic content where parts of the email literally change for each person. And stresses that even with all this automation, you still need to ab test your personalization strategies.
Does predicting their next purchase actually work better? Test it, right? Always test and keeping the human touch in email crucial. Use authentic language. Don’t overdo the personalization token so it sounds creepy. Make sure the context makes sense, and AI also helps improve automated sequences, making the branching logic smarter based on clicks or website visits, inserting dynamic content, optimizing timing, and figuring out the best way to re-engage people who’ve gone quiet. So making email automation much more adaptive and well intelligent. Let’s switch gears slightly to influencer marketing. How does AI play a role there? Right. Influencer marketing, the journey points out the old struggles.
Finding the right people takes ages, sending generic emails gets ignored. Yeah, tell me about it. So AI tools like Upfluence or CreatorIQ (formerly AspireIQ) are highlighted. They help you discover influencers based on keywords, audience, data, engagement rates much faster. AI can also help vet influencers looking for signs of fake followers or inflated engagement, authenticity, analysis. Nice. Yeah. Plus, AI can assist in writing more personalized outreach messages, maybe even automating follow ups, and then tracking the campaign, measuring reach, engagement, sentiment, ROI, AI helps manage and analyze that data too. It even mentions using AI to brainstorm content ideas or draft briefs for the influencers.
Okay, so streamlining discovery, outreach, and measurement. That makes sense. Now across all these areas, content, SEO, social email influencers, we’re using AI tools. How do we know if it’s actually working? The measurement and ROI piece, absolutely fundamental. The learning journey really stresses this. You need clear goals first, smart goals. Specific, measurable, achievable, relevant, time bound. What are you trying to achieve with AI and SEO? Or AI and email to find that first. Okay. Then identify the right key performance indicators, KPIs, it gives examples for different channels. Social media engagement like likes, shares, comments, blog metrics like time on page, bounce rate, email opens, clicks, replies, standard stuff, but focused on the AI impact. Exactly. And it highlights AI powered analytics tools, especially for social, that go beyond just counting things. They help understand why content performs, how audiences behave, even the emotional tone surrounding your brand, deeper insights.
Yes, the core message is, the ROI of your AI initiatives. Are you spending money on an AI content tool?
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